A method for the rapid and simultaneous determination of carbendazim and thiabendazole residues by electrospray ionization-ion mobility spectrometry (ESI-IMS) combined with a metal ion-assisted technique was developed and validated in different fruit matrices. The metal ion assisted strategy was performed instead of tedious pre-separation procedures to overcome the limitation of low resolution of IMS. Four transition metal cations, Co(II), Ni(II), Cu(II), and Zn(II), were screened and their interactions with carbendazim and thiabendazole were investigated. The injection flow rate and metal ion concentration were optimized. The Cu(II) assisted approach helped to achieve well-separated peaks with a peak-to-peak resolution of 3.61. This method was then applied to detect carbendazim and thiabendazole simultaneously in apples, pears, bananas, and mangoes. The limit of detection (LOD) were 0.03 mg kg-1 and 0.13 mg kg-1 for carbendazim and thiabendazole, respectively, while spiked recoveries were 61.5-122.0% and 83.5-119.8%, respectively, with RSDs less than 13.9%. These satisfactory evaluation parameters indicated that the approach was capable of performing quantitative analysis of multi-pesticide residues. In addition, the feasibility of using metal ion assisted-ESI-IMS for the simultaneous detection also was theoretically demonstrated through molecular electrostatic potential analysis and binding energy calculation based on density functional theory (DFT). Both experimental and theoretical results revealed the effectiveness of the metal ion assisted strategy in improving the resolution of ESI-IMS.

The selectivity in the simultaneous detection of ascorbic acid (AA), dopamine (DA), and uric acid (UA) has been an open problem in the biosensing field. Many surface modification methods were carried out for glassy carbon electrodes (GCE), including the use of graphene oxide and amino acids as a selective layer. In this work, molecular dynamics (MD) simulations were performed to investigate the role of serine oligomers on the selectivity of the AA, DA, and UA analytes. Our models consisted of a graphene oxide (GO) sheet under a solvent environment. Serine tetramers were added into the simulation box and were adsorbed on the GO surface. Then, the adsorption of each analyte on the mixed surface was monitored from MD trajectories. It was found that the adsorption of AA was preferred by serine oligomers due to the largest number of hydrogen-bond forming functional groups of AA, causing a 10-fold increase of hydrogen bonds by the tetraserine adsorption layer. UA was the least preferred due to its highest aromaticity. Finally, the role of hydrogen bonds on the electron transfer selectivity of biosensors was discussed with some previous studies. AA radicals received electrons from serine through hydrogen bonds that promoted oxidation reaction and caused the negative shifts and separation of the oxidation potential in experiments, as DA and UA were less affected by serine. Agreement of the in vitro and in silico results could lead to other in silico designs of selective layers to detect other types of analyte molecules.

With the goal of accurately detecting and quantifying the amounts of dopamine (DA) and serotonin (5-HT) in mixtures of these neurotransmitters without using any labelling, we present a detailed, comparative computational and Raman experimental study. Although discrimination between these two analytes is achievable in such mixtures for concentrations in the millimolar range, their accurate quantification remains unattainable. As shown for the first time in this work, the formation of a new composite resulting from their interactions with each other is the main reason for this lack of quantification. While this new hydrogen-bonded complex further complicates potential analyte discrimination and quantification at concentrations characteristic of physiological levels (i.e., nanomolar concentrations), it can also open new avenues for its use in drug delivery and pharmaceutical research. This remark is based not only on chemical interactions analyzed here from both theoretical and experimental approaches, but also on biological relationship, with consideration of both functional and neural proximity perspectives. Thus, this research constitutes an important contribution toward better understanding of neural processes, as well as toward possible future development of label-free biosensors.

Sunlight assisted reduction of silver ions were accomplished for the synthesis of silver nanoparticles incorporated within the mesoporous silicate framework of zeolite Y. The zeolite-Y and AgNP/Zeo-Y were characterized by field emission scanning electron microscopy, transmission electron microscopy, N2 adsorption-desorption BET isotherm and X-ray diffraction techniques. The incorporation of silver nanoparticles within the porous framework was further confirmed by cyclic voltammetry and electrochemical impedance spectroscopy. An enhanced electrocatalytic oxidation of biologically important molecules like dopamine and uric acid using AgNP/Zeo-Y modified glassy carbon electrode has been developed. A simultaneous oxidation of DA and UA peaks were obtained at +0.31V and +0.43V (vs. Ag/AgCl) using AgNP/Zeo-Y/GCE under the optimum experimental condition. A well-resolved peak potential window (~120mV) for the oxidation of both DA and UA were observed at AgNP/Zeo-Y/GCE system. The calibration curves for DA and UA were obtained within the dynamic linear range of 0.02×10(-6) to 0.18×10(-6)M (R(2)=0.9899) and 0.05×10(-6) to 0.7×10(-6)M (R(2)=0.9996) and the detection limits were found to be 1.6×10(-8)M and 2.51×10(-8)M by using differential pulse voltammetry (DPV) method. The proposed method was successfully applied for the determination of both DA and UA in human urine samples with a related standard deviation was <3%, and n=5 using the standard addition method.